To our knowledge, DeepScene [1]} is the first public off-road dataset for multispectral segmentation collected in unstructured forest environments. YCOR [2]} is a more diverse and challenging dataset than DeepScene. However, both DeepScene and YCOR have small amount of data. RUGD [3]} was collected in an off-road environment for RGB image semantic segmentation task but only has one modality data. RELLIS-3D Dataset [4]} improves RUGD with multi-modal sensor to enhance autonomous navigation in off-road environments. The above datasets do not focus on the analysis of traversability in off-road environments, while the detection of traversable area, namely freespace, is one of the most important modules for autonomous driving, especially in off-road environments. In our work, we create the first dataset with accurate and complete ground truths for off-road freespace detection.
